How do you ensure data consistency and durability in cloud-native applications?

In a cloud-native environment, data consistency refers to the accuracy of data synchronization among multiple services, and persistence ensures that data is not lost in storage. Its importance lies in maintaining the integrity and reliability of application states, applied in scenarios such as microservice architectures and e-commerce systems to avoid data errors and service interruptions.

The core includes using persistent storage solutions such as Kubernetes' Persistent Volumes and data replication mechanisms, combined with microservice patterns to handle consistent transactions (e.g., Saga or CQRS). In practical applications, permanent data storage is achieved by configuring PVC (Persistent Volume Claims) in Kubernetes, with database replication and high-availability design. The impacts include improving system fault tolerance, supporting disaster recovery, and reducing the risk of data conflicts.

Implementation steps: 1. Deploy persistent storage such as object storage or volume plugins. 2. Apply transaction consistency patterns (e.g., event sourcing). 3. Set up backup strategies and monitoring. A typical scenario is an order processing system; the business value lies in ensuring data security, enhancing user experience and compliance, and reducing operational costs.